The present invention relates to display color gamut mapping and image color enhancement.
An image color enhancement algorithm maps color of an image to new more saturated colors. Image color enhancement is also a three dimensional mapping technique. The input of color enhancement is 3 dimensional and the output is 3 dimensional.
The advance of flat panel display (FPD) technology is able to make the color gamut of a display wider than the sRGB/ITU-R BT.709 color gamut that is widely used by the current HDTV and Internet/computers standards. A color gamut mapping algorithm (GMA) maps RGB (red, blue, green) display values of a color in a color gamut to new RGB values in a new gamut. The RGB display values before and after a GMA usually are different, and may or may not represent the same physical color. The input of a GMA is also 3 dimensional and the output of a GMA is also 3 dimensional.
A GMA from small gamut to big gamut is an image color enhancement algorithm, and has the same challenges as an image color enhancement algorithm without a display gamut change Most existing current image color enhancement techniques typically boost saturation of colors while keeping the colors' hue substantially unchanged. In the hue-saturation color wheel such as the one shown in FIG. 1, a typical color enhancement technique moves colors outward on the radial direction as shown by the arrows. Essentially, the color enhancement algorithm increases the input images' dynamic range by increasing the color saturation of the pixels.
The techniques used to enhance the color enhancement of an image are based upon modification of individual pixels. When the color of a pixel is enhanced to a new color, the conversion from the old color to the new color for each pixel is a predetermined fixed adjustment for the entire image or for the entire video.
By way of example, televisions have built-in color enhancement techniques to enhance unsaturated colors in certain content and let viewers set their color preferences. Because the human eye is very sensitive to the skin color, it is important for a color enhancement technique to render skin colors properly. If they are essentially calibrated at the input, then they are generally not increased in saturation. Preventing this change in saturation of skin colors can be called protection from saturation or simply saturation. It is also desirable for a color enhancement technique to separately adjust skin colors and non-skin colors using different characteristics.
Some color enhancement techniques have the capability of protecting skin colors. These techniques are typically pixel-based. When the color of a pixel is enhanced to a new color, the conversion from the old color to the new color is fixed, and is not affected by other pixels. Because pixel-based color enhancement techniques with skin color protection cannot overcome the issue that the colors of skin and non-skin are highly overlapped, these techniques cannot effectively protect skin tones to maintain their calibration with the input image.
The pixel-based algorithms do not work effectively. Specifically, to avoid generating visible contouring artifacts in the areas of an image where skin and neighboring non-skin colors are mixed, both the skin color region in the color space and the gradual transition region between the skin color region and the non-skin color region have to be set very wide. Typically, the skin color and transition regions cover nearly half of the color gamut, as illustrated in FIG. 2. On the other hand, some true skin colors are missed in the skin color region and therefore remain unprotected. Consequently, many non-skin colors are improperly protected while many skin colors are improperly enhanced by the enhancement techniques.